The Commercialization of The Domestic AI industry in 2022
Artificial intelligence (AI), which refers to the ability of machines to stimulate thinking within a narrow context to perform specific tasks, is driving massive shifts across the world. The field of AI is broad and dynamic, and it is hard to define the global and societal implications of AI. Exploring the scope and activity within this extensive field can help national policymakers, entrepreneurs, researchers and the public to clarify AI technology and understand how it works. This report mainly focuses on the Chinese AI industry, which is now on the global frontier regarding technological development and market applications. The structure of the report is as follows. In the first section, Equal Ocean will provide an overview of national policies and development in the AI industry. Section two describes the business applications of AI in different fields. In section three, Equal Ocean will discuss the evolution of Chinese AI companies. Finally, Equal Ocean suggests challenges and opportunities for future AI development.
An overview of Chinese AI policies and development
Artificial intelligence's growing importance and relevance to technological innovation are undisputed in the digital age. Since 2016, the development of AI has been increasingly embedded in more than 40 countries' national strategies, and governments have started to see artificial intelligence as a nation-defining capability. Under the impact of the Covid-19 pandemic, an increasing number of countries have recognized that AI plays a crucial role in enhancing global competitiveness and have decided to create formal national AI frameworks. Countries that aren't investing in the AI industry risk becoming obsolete.
In recent years, America, China, the European Commission, Japan and the UK have all invested substantial financial resources to promote the use of AI and released official strategies to address future development of the AI industry. However, countries are taking vastly different approaches to develop AI technology. For instance, America laid out its plan for global dominance and established a national artificial intelligence bureau. The European Commission proposed several federal guidelines for promoting digitalization in European countries. UK released the next 10-year AI strategy, aiming to regain its influence in the field of AI. Japan is the first country to focus on using AI to enhance government performance.
At the same time, China pledged billions in direct AI research spending and planned to lead the world in AI technology by 2035. Chinese AI industry is still experiencing rapid growth in many indicators, and the business environment has remained favorable until now.
The booming development of the Chinese AI industry could contribute to various aspects, such as solid policy support, continuous technology breakthrough in deep learning, diverse market-driven applications and successful commercialization. The Chinese government also actively embraces the metaverse and recognizes it as a critical focus of future AI development. As estimated by the Equal Ocean, Chinese local governments realized more than 20 metaverse-related policies to guide future AI development this year. Such policies include, but are not limited to, "The 14th Five-Year Plan," "White Paper for the development of the metaverse," "Action outlines for promoting software and information technology," and "Blue Paper for artificial intelligence education (2022)".
China's global share of research papers in the field of AI has vaulted from 18% in 2017 to 22.4% in 2021, surpassing any other country in the world, including the U.S. However, the US achieved AI dominance in terms of enacting rules and development direction. China also consistently files more AI patents than any other country. As of 2021, the number of Chinese AI patents has reached 400,000, comprising more than 75% of world AI patents. Such impressive achievements could translate into China's full advantage in AI innovation and global leadership. These policies also signal to AI entrepreneurs, researchers and investors that AI is backed by the government and worth investing in.
The business application of AI in various fields
Improving product and service quality through AI undoubtedly leads to immense fiscal benefits for the Chinese economy. AI applications are typical in many activities. In the finance sector, AI is deeply involved in business processes to design financial products, marketing and customer service. In the field of smart cities, the use of AI contributes to increased living standards, mass data analysis and security issues. In the manufacturing sector, AI facilitates product design, production and logistics. AI is also used in autonomous driving to ensure accurate driving paths and digital assistants. Similarly, AI is widely used in service sectors to maximize working efficiency and increase profitability.
Overall, AI as a field brings together several domains—finance, smart city, manufacturing, biology, robot and autonomous driving, which in return speed up AI discoveries and open more possibilities.
AI + Finance: Traditionally, financial processes heavily depend on manual effort, which is time-consuming and costly. AI tools open new ways to centralize and standardize financial functions and can be more consistent in terms of lending, borrowing, saving, budgeting, forecasting and investing. While AI technologies revolutionize the way the financial world operates, policymakers also need to consider regulation and compliance factors when implementing this new tool.
AI + Smart City: A smart city is a modern urban area that relies on electronic methods such as the Internet of things, cloud computing, artificial intelligence, big data and geospatial information to manage assets, resources and services efficiently. The application of AI could be seen in many smart city scenarios such as security, transportation, government affairs, social services, tourism and consumption, especially in the environment where the camera is heavily equipped. Overall, AI-equipped cities with advanced features helped habitats enjoy a safer and more convenient life.
AI+Manufacturing: "AI+Industrial Internet" will help companies improve product quality and working efficiency. In recent years, China put great efforts into promoting the manufacturing industry's digital transformation. As AI is an essential part of this transformation, it has been involved in multiple manufacturing steps such as production, warehousing, logistics, supply chain, after-sales and other aspects.
AI+ Medical filed: AI-based medical solutions can effectively streamline the diagnosis and treatment process through a large amount of structured and unstructured medical data, thereby providing hospitals and health systems with real-time, data-driven decision aids. AI is widely used in scenarios such as electronic medical records, imaging diagnosis, remote diagnosis, medical robotics, new drug development and gene sequencing, becoming an essential factor in the healthcare industry and improving relevant services.
AI+Robot: Robots could integrate multiple AI technologies, including semantic recognition, natural language processing, speech synthesis and computer vision. Robots are used in various areas such as factories, households, hotels, restaurants and shopping malls. With the increasing cost of labor forces, intelligent robots will be implemented as a perfect substitution to perform manual tasks and improve working efficiency.
AI+ Autonomous driving: China's autonomous driving is currently in the transition period from the first stage (independent development) to the second stage (collaborative development), with the main focus on the development of the "vehicle-road-cloud" system. China is increasingly constructing intelligent transportation, communication base stations and cloud control platforms to promote autonomous driving technology. Additionally, the continuous investment in intelligent network technologies could guarantee the success of the "vehicle-road-cloud" system.
Artificial intelligence companies in China
The world witnessed the exponential growth of the Chinese AI industry in the past decade. The wave of Chinese artificial entrepreneurship emerged between 2014 and 2018 under favorable policies. However, investments showed a continuous decline in 2019-2020. The amount of financing shows a significant growth in 2020, indicating that some AI companies may hit the stage of maturity.
Most Chinese AI companies are located in Beijing, Shanghai, Guangzhou, Zhejiang and Jiangsu due to the access to excellent local talent pools, robust research and development bases and ambitious local policy support. Speechocean, SenseTime, innovation and other companies completed the listing between 2021 and 2022. CloudWalk Technology Co. Ltd, Intellifusion, Transwarp Technology（Shanghai）Co., Ltd and Other Chinese AI companies are proceeding with plans for IPOs, with listings mainly on the Hong Kong, Shenzhen and Shanghai stock exchanges. More IPOs are certainly expected from leading Chinese AI companies later this year.
Currently, most Chinese AI companies focus on finance, robotics, intelligent transportation, and smart manufacturing, while less attention is given to the tourism, electricity, and education industries. Due to the vast market demand, most Chinese AI companies put great efforts into developing big data and cloud computing technology. However, many companies are working on technologies such as machine learning and reasoning, IoT, and industrial robotics.
It is worth mentioning that computer vision is currently the leading AI application, and the IPO pipelines are heavily concentrated in AI vision-related companies due to more mature technology development and higher commercialization potential.
Future challenges and trends for the AI industry
AI is no longer an independent technology, and an increasing number of companies approach AI in an interdisciplinary way. Integrating AI with many traditional industries could lead to more possibilities. Besides the Internet, finance and other sectors that are naturally more suitable for AI applications, conventional enterprises are vigorously embracing this technology. Taking the manufacturing industry as an example, steel and energy companies are actively introducing AI tools to reduce production costs and improve efficiency. Undoubtedly, many traditional industries would continue to point out the future AI development direction. Furthermore, as artificial intelligence is an integral piece of the metaverse puzzle, it unlocks insights for tech companies to expand their business maps, generating new revenue streams.
While the opportunities of AI are great, there are risks involved. Poor-quality AI data and the lack of computing power are two prominent challenges of implementing AI on a large scale.
Firstly, AI makes decisions based on algorithms, which require reviewing large amounts of data to identify and follow patterns. Therefore, high-quality data is necessary for AI to perform efficiently. However, the current AI capabilities often cannot distinguish trustable and clean data between low-quality and inaccurate data. More importantly, large volumes of data bring the problem of data leakage and relevant security issues, which simultaneously require strict data management environment and continuous AI algorithm training.
Secondly, achieving the computing power to process the inflow of ever-increasing amounts of data can be pretty challenging, especially for start-ups or tight-budget local governments. The price of having such unprecedented computing power could keep most industries away.
On the other hand, these two factors suggest the future development direction of AI technology: focusing on vertical industry and adopting data-reuse adaptive algorithms to increase the affordability of AI.
The low data-reuse rate due to fragmented scenes leads to the high cost of AI implementation. However, companies could quickly resolve this problem if they only focus on vertical industry and manufacture more standardized and customized products. Integrating scenarios with high repetition and forming standardized products will effectively contribute to a data-reuse adaptive algorithm and reduce relevant costs. Overall, it is better to focus on vertical fields and provide more specific products and services for companies that plan to introduce AI to their business model.
This article contains only excerpts from the report. For more details, please click to download the full report here.